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A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-04
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
We propose filtering the PET sinograms with a constraint curvature motion diffusion.
The edge-stopping function is computed in terms of edge probability under the assumption of contamination by Poisson noise.
We show that the Chi-square is the appropriate prior for finding the edge probability in the sinogram noise-free gradient.
Since the sinogram noise is uncorrelated and follows a Poisson distribution, we then propose an adaptive probabilistic diffusivity function where the edge probability is computed at each pixel.
The filter is applied on the 2D sinogram prereconstruction.
The PET images are reconstructed using the Ordered Subset Expectation Maximization (OSEM).
We demonstrate through simulations with images contaminated by Poisson noise that the performance of the proposed method substantially surpasses that of recently published methods, both visually and in terms of statistical measures.
American Psychological Association (APA)
Alrefaya, Musa& Sahli, Hichem. 2013. A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-14.
https://search.emarefa.net/detail/BIM-494288
Modern Language Association (MLA)
Alrefaya, Musa& Sahli, Hichem. A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram. Journal of Applied Mathematics No. 2013 (2013), pp.1-14.
https://search.emarefa.net/detail/BIM-494288
American Medical Association (AMA)
Alrefaya, Musa& Sahli, Hichem. A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-14.
https://search.emarefa.net/detail/BIM-494288
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-494288